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Groundnut productivity and quality have been impeded by rising temperatures in semi-arid environments. Hence, understanding the effects and molecular mechanisms of heat stress tolerance will aid in tackling yield losses. In this context, a recombinant inbred line (RIL) population was developed and phenotyped for eight seasons at three locations for agronomic, phenological, and physiological traits under heat stress. A genetic map was constructed using genotyping-by-sequencing with 478 single-nucleotide polymorphism (SNP) loci spanning a map distance of 1,961.39 cM. Quantitative trait locus (QTL) analysis using phenotypic and genotypic data identified 45 major main-effect QTLs for 21 traits. Intriguingly, three QTL clusters (Cluster-1-Ah03, Cluster-2-Ah12, and Cluster-3-Ah20) harbor more than half of the major QTLs (30/45, 66.6%) for various heat tolerant traits, explaining 10.4%-38.6%, 10.6%-44.6%, and 10.1%-49.5% of phenotypic variance, respectively. Furthermore, important candidate genes encoding DHHC-type zinc finger family protein ( arahy.J0Y6Y5 ), peptide transporter 1 ( arahy.8ZMT0C ), pentatricopeptide repeat-containing protein ( arahy.4A4JE9 ), Ulp1 protease family ( arahy.X568GS ), Kelch repeat F-box protein ( arahy.I7X4PC ), FRIGIDA-like protein ( arahy.0C3V8Z ), and post -illumination chlorophyll fluorescence increase ( arahy.92ZGJC ) were the underlying three QTL clusters. The putative functions of these genes suggested their involvement in seed development, regulating plant architecture, yield, genesis and growth of plants, flowering time regulation, and photosynthesis. Our results could provide a platform for further fine mapping, gene discovery, and developing markers for genomics-assisted breeding to develop heat-tolerant groundnut varieties., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Sharma, Gangurde, Nayak, Gowda, Sukanth, Mahadevaiah, Manohar, Choudhary, Anitha, Malavalli, Srikanth, Bajaj, Sharma, Varshney, Latha, Janila, Bhat and Pandey.)

With an objective of identifying the genomic regions for productivity and quality traits in peanut, a recombinant inbred line (RIL) population developed from an elite variety, TMV 2 and its ethyl methane sulfonate (EMS)-derived mutant was phenotyped over six seasons and genotyped with genotyping-by-sequencing (GBS), Arachis hypogaea transposable element (AhTE) and simple sequence repeats (SSR) markers. The genetic map with 700 markers spanning 2,438.1 cM was employed for quantitative trait loci (QTL) analysis which identified a total of 47 main-effect QTLs for the productivity and oil quality traits with the phenotypic variance explained (PVE) of 10-52% over the seasons. A common QTL region (46.7-50.1 cM) on Ah02 was identified for the multiple traits, such as a number of pods per plant (NPPP), pod weight per plant (PWPP), shelling percentage (SP), and test weight (TW). Similarly, a QTL (7.1-18.0 cM) on Ah16 was identified for both SP and protein content (PC). Epistatic QTL (epiQTL) analysis revealed intra- and inter-chromosomal interactions for the main-effect QTLs and other genomic regions governing these productivity traits. The markers identified by a single marker analysis (SMA) mapped to the QTL regions for most of the traits. Among the five potential candidate genes identified for PC, SP and oil quality, two genes ( Arahy.7A57YA and Arahy.CH9B83 ) were affected by AhMITE1 transposition, and three genes ( Arahy.J5SZ1I, Arahy.MZJT69 , and Arahy.X7PJ8H ) involved functional single nucleotide polymorphisms (SNPs). With major and consistent effects, the genomic regions, candidate genes, and the associated markers identified in this study would provide an opportunity for gene cloning and genomics-assisted breeding for increasing the productivity and enhancing the quality of peanut., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Jadhav, Gangurde, Hake, Yadawad, Mahadevaiah, Pattanashetti, Gowda, Shirasawa, Varshney, Pandey and Bhat.)

Foliar fungal diseases especially late leaf spot (LLS) and rust are the important production constraints across the peanut growing regions of the world. A set of 340 diverse peanut genotypes that includes accessions from gene bank of International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), elite breeding lines from the breeding program, and popular cultivars were screened for LLS and rust resistance and yield traits across three locations in India under natural and artificial disease epiphytotic conditions. The study revealed significant variation among the genotypes for LLS and rust resistance at different environments. Combined analysis of variance revealed significant environment (E) and genotype × environment (G×E) interactions for both the diseases indicating differential response of genotypes in different environments. The present study reported 31 genotypes as resistant to LLS and 66 to rust across the locations at 90 DAS with maturity duration 103 to 128 days. Twenty-eight genotypes showed resistance to both the diseases across the locations, of which 19 derived from A. cardenasii , five from A. hypogaea , and four from A. villosa. Site regression and Genotype by Genotype x Environment (GGE) biplot analysis identified eight genotypes as stable for LLS, 24 for rust and 14 for pod yield under disease pressure across the environments. Best performing environment specific genotypes were also identified. Nine genotypes resistant to LLS and rust showed 77% to 120% increase in pod yield over control under disease pressure with acceptable pod and kernel features that can be used as potential parents in LLS and rust resistance breeding. Pod yield increase as a consequence of resistance offered to foliar fungal diseases suggests the possibility of considering 'foliar fungal disease resistance' as a must-have trait in all the peanut cultivars that will be released for cultivation in rainfed ecologies in Asia and Africa. The phenotypic data of the present study will be used for designing genomic selection prediction models in peanut., (Copyright © 2019 Chaudhari, Khare, Patil, Sundravadana, Variath, Sudini, Manohar, Bhat and Pasupuleti.)

The aim of this study was to identify candidate resistance genes for late leaf spot (LLS) and rust diseases in peanut ( Arachis hypogaea L.). We used a double-digest restriction-site associated DNA sequencing (ddRAD-Seq) technique based on next-generation sequencing (NGS) for genotyping analysis across the recombinant inbred lines (RILs) derived from a cross between a susceptible line, TAG 24, and a resistant line, GPBD 4. A total of 171 SNPs from the ddRAD-Seq together with 282 markers published in the previous studies were mapped on a genetic map covering 1510.1 cM. Subsequent quantitative trait locus (QTL) analysis revealed major genetic loci for LLS and rust resistance on chromosomes A02 and A03, respectively. Heterogeneous inbred family-derived near isogenic lines and the pedigree of the resistant gene donor, A. cardenasii Krapov. & W.C. Greg., including the resistant derivatives of ICGV 86855 and VG 9514 as well as GPBD 4, were employed for whole-genome resequencing analysis. The results indicated the QTL candidates for LLS and rust resistance were located in 1.4- and 2.7-Mb genome regions on A02 and A03, respectively. In these regions, four and six resistance-related genes with deleterious mutations were selected as candidates for LLS and rust resistance, respectively. These delimited genomic regions may be beneficial in breeding programs aimed at improving disease resistance and enhancing peanut productivity.